Sex differences in factors predicting post‐treatment opioid use.
Background and aims: Several reports have documented risk factors for opioid use following treatment discharge, yet few have assessed sex differences, and no study has assessed risk using contemporary machine learning approaches. The goal of the present paper was to inform treatments for opioid use...
| Publicado en: | Addiction Vol. 116; no. 8; pp. 2116 - 2127 |
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| Autores principales: | , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Aug2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151210167&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151210167 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: Aug2021 vid: 116 iid: 8 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 151210167 148223828 151210167 151210167 10.1111/add.15396 151210167 ppf: 2116 ppct: 11 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Sex differences in factors predicting post‐treatment opioid use. aug: au: Davis, Jordan P. Eddie, David Prindle, John Dworkin, Emily R. Christie, Nina C. Saba, Shaddy DiGuiseppi, Graham T. Clapp, John D. Kelly, John F. affil: Suzanne Dworak‐Peck School of Social Work, USC Center for Artificial Intelligence in Society, USC Center for Mindfulness Science, USC Institute for Addiction Science, University of Southern California, Los Angeles CA,, USA sug: subj: Substance Use Disorders Therapy Sex Factors Attitude to Medical Treatment Forecasting Human Male Female Secondary Analysis Adolescence Adult Treatment Outcomes Odds Ratio Descriptive Statistics Age Factors Adolescent: 13-18 years Adult: 19-44 years Male Female ab: Background and aims: Several reports have documented risk factors for opioid use following treatment discharge, yet few have assessed sex differences, and no study has assessed risk using contemporary machine learning approaches. The goal of the present paper was to inform treatments for opioid use disorder (OUD) by exploring individual factors for each sex that are most strongly associated with opioid use following treatment. Design Secondary analysis of Global Appraisal of Individual Needs (GAIN) database with follow‐ups at 3, 6 and 12 months post‐OUD treatment discharge, exploring demographic, psychological and behavioral variables that predict post‐treatment opioid use. Setting One hundred and thity‐seven treatment sites across the United States. Participants: Adolescents (26.9%), young adults (40.8%) and adults (32.3%) in treatment for OUD. The sample (n = 1,126) was 54.9% male, 66.1% white, 20% Hispanic, 9.8% multi‐race/ethnicity, 2.8% African American and 1.3% other. Measurement Primary outcome was latency to opioid use over 1 year following treatment admission. Results: For women, regularized Cox regression indicated that greater withdrawal symptoms [hazard ratio (HR) = 1.31], younger age (HR = 0.88), prior substance use disorder (SUD) treatment (HR = 1.11) and treatment resistance (HR = 1.11) presented the largest hazard for post‐treatment opioid use, while a random survival forest identified and ranked substance use problems [variable importance (VI) = 0.007], criminal justice involvement (VI = 0.006), younger age (VI = 0.005) and greater withdrawal symptoms (VI = 0.004) as the greatest risk factors. For men, Cox regression indicated greater conduct disorder symptoms (HR = 1.34), younger age (HR = 0.76) and multiple SUDs (HR = 1.27) were most strongly associated with post‐treatment opioid use, while a random survival forests ranked younger age (VI = 0.023), greater conduct disorder symptoms (VI = 0.010), having multiple substance use disorders (VI = 0.010) and criminal justice involvement (VI = 0.006) as the greatest risk factors. Conclusion: Risk factors for relapse to opioid use following opioid use disorder treatment appear to be, for women, greater substance use problems and withdrawal symptoms and, for men, younger age and histories of conduct disorder and multiple substance use disorder. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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